## Tracking in Practice

We have seen two broad methods used in class.

1.  Find feature and draw a bounding box, for each frame independently.  
2.  Using the temporal derivative to estimate motion.

The first approach disregards the *history* completely.  The result is that it does not always find the same points in every frame.  Drawing the bounding box, one will see it jumping to a different object in some frames.

The second approach uses *only* the history.  Since there is a lot of noise and approximation in the problem, it is not going to be perfect.  If a feature point is lost, we may end up tracking from a non-feature point where $G$ is not invertible.

In practice, one will have to combine approaches, if it is necessary to identify and track individual objects.  There are other tools in the box:

3.  Feature Descriptors can be used to match features between frames.  We shall discuss [SIFT]() tomorrow.
4.  Other heuristics can be used to identify objects (i.e. objects bounded by more than one feature point/edges).

Complete mastery or solution of particular practical problems are beyond the scope of a 7½ point module, but could be a suitable final year project for next semester.  In this module, the goal is to understand some of the building blocks in sufficient depth to be able to tweak and combine them when needed.  The solutions to each of the toy problems we solve are not that important.  The experience is what is important.